Two‐vector based low‐complexity model predictive flux control for current‐source inverter‐fed induction motor drive

Abstract

Model predictive control is an effective approach to achieve high performance on electric motor drives. In this study, a two‐vector based low‐complexity model predictive flux control (TVLC‐MPFC) is proposed and introduced for low power current‐source inverter (CSI)‐fed induction motor (IM) drive. In contrast to conventional two‐vector based model predictive flux control (TV‐MPFC), TVLC‐MPFC is a more simplified scheme with a lower calculation burden, which eliminates the requirement on the iteration procedures to obtain the results of the optimal current vector combination with optimal dwell time. Moreover, since TVLC‐MPFC avoids the possibility of selecting the wrong vector combination in some cases, which would happen with conventional TV‐MPFC, it presents better output performance than TV‐MPFC. The robustness of TVLC‐MPFC under parameter uncertainty is discussed as well. Experimental tests are carried out on a low power CSI‐fed IM drive (5 kW/208 V/14.3 A) and verify the effectiveness of the proposed scheme.

Two‐stage DSVM‐based torque ripple minimisation technique for the predictive torque control of the induction motor

“…In recent years, the Model Predictive Control (MPC) method, especially Finite Control Set MPC (FCS-MPC), has been the subject of many investigations in the field of power converters and drive systems, due to the discrete nature of these converters [1,2]. Generally, FCS-MPC predicts the future performance of the system based on evaluating all possible switching states, and selects the most efficient one in terms of realising control goals.…”